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update model card README.md

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@@ -19,7 +19,7 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.7291704844896334
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5961
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- - F1: 0.7292
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5.1956060024552943e-05
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- - train_batch_size: 64
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- - eval_batch_size: 64
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- - seed: 0
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 4
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | 0.7439 | 1.0 | 51 | 0.6396 | 0.6592 |
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- | 0.4792 | 2.0 | 102 | 0.5564 | 0.7408 |
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- | 0.2576 | 3.0 | 153 | 0.5768 | 0.7355 |
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- | 0.2065 | 4.0 | 204 | 0.5961 | 0.7292 |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.732897530282475
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0989
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+ - F1: 0.7329
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5.18796906442746e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - num_epochs: 4
 
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.3703 | 1.0 | 408 | 0.6624 | 0.7029 |
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+ | 0.2122 | 2.0 | 816 | 0.6684 | 0.7258 |
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+ | 0.9452 | 3.0 | 1224 | 1.0001 | 0.7041 |
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+ | 0.0023 | 4.0 | 1632 | 1.0989 | 0.7329 |
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  ### Framework versions